Hi Martin,
A few remarks:
- As pointed by Kit Baum, the "within" or "fixed effect" estimator implemented in -xtivreg, fe- is not consistent in the case of a DPD model. If there is a lag of the dependent variable on the RHS of your equation, you should never, ever use -xtivreg, fe- :)
- The Anderson-Hsiao estimator is consistent for T->infty, N->infty, or both. Unfortunately, the -xtivreg, fd- implementation of this estimator cannot be used for inference and hypothesis testing. The problem is that the Anderson-Hsiao (or Arellano-Bond, for that matter) orthogonality conditions involving lags of the dependent variable are only valid when the error term in the levels equation is not serially correlated. However, when the error term in the levels equation is not serially correlated, the error term in the first-difference equation exhibits negative first-order autocorrelation. Unfortunately, the Anderson-Hsiao estimator relies on the first-difference equation, and -xtivreg, fd- does not report robust standard deviations for the coefficients.
- The Arellano-Bond GMM estimator is a random-effect estimator in the sense that the individual effect is treated as a random variable. However, like the "within fixed effect" estimator implemented in -xtivreg, fe-, the Arellano-Bond estimator is perfectly valid when the individual effect is correlated with some of the regressors (or even all the regressors). Any estimator that relies on first-differencing or orthogonal deviations can cope with the correlation between the individual effect and the regressors. In contrast, the estimators implemented in -xtivreg, re- are not valid when the individual effect is correlated with some of the regressors.
- As I said in my response to Edlira, additional consistency results for the GMM DPD estimators are provided in the recent paper by Alvarez and Arellano (2003), "The time-series and cross-section asymptotics of dynamic panel data estimators", Econometrica, July. Check it out. You might be happily surprised :)
Jean Salvati
Econometric Support
(202) 623-7804
IS 12-1328
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of
> Martin Mathes
> Sent: Sunday, October 17, 2004 12:57 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Macoreconometric dynamic panels (was: Re: st: panel
> autocorrelation)
>
> Dear Christopher, dear Listers,
>
> the topic of our discussion is moving slightly towards a very
> interesting (and fundamental) question:
>
> What estimator to apply in case of a macroeconometric (!)
> dynamic panel?
>
> I haven't mentioned that my panel is a macroeconometric one
> so (1) it tends to T>N and (2) fixed effects can be assumed
> to be more adequate than random effects (in the case of
> absence of LDVs).
> The following considerations led me to employ xtreg, fe
> or/and xtivreg:
> In the case of large T the FE-estimator is consistent (cf eg
> Bond [p. 5, fn 6]). Employing RE instead of FE can afaik be
> assumed to lead to a bias in a case in which FE should
> obviously be the prefered estimator.
> Furthermore, the paper "Estimating Dynamic Panel Data Models:
> A Practical Guide for Macroeconomists" by Judson/Owen
> (http://papers.ssrn.com/sol3/Delivery.cfm/Delivery.cfm/9705013.pdf?a
> bstractid=1904&mirid=1) concludes after running a Monte Carlo
> analysis comparing variants of Arellano-Bond-GMMs and
> Anderson- Hsiao-ivregs that with small Ns the latter
> outperform the first. (Their tab 4 indicates that with *very*
> small N even OLS-FE outperforms AB- GMM, at least as far as I
> have understood.)
>
> It seems to me that - in general - there might be a conflict
> between a panel's quality of beeing a macroeconometric one
> (-> xtreg fe or something xtivreg-like preferable) and a
> dynamic one (-> xtabond preferable). Could including
> group-dummies in a xtabond-estimation provide a solution? I
> haven't seen this to be done or discussed yet.
>
> As I am really no expert on this (at least so far...), I
> would appreciate your (and the listers') comments on this
> issue very much.
>
> And last but not least: If I kept my initial choice of
> estimators, would there be any possibility to test for autocorr?
>
> Martin
>
>
> > Drop the notion of the fixed effects estimator. It does not
> make sense
> > in a dynamic context (for good reason, as any paper underlying the
> > Arellano-Bond approach indicates) as an OLS technique is unable to
> > cope with the correlation between the demeaned LDV and the demeaned
> > error process. (You would run into the same trouble if you did the
> > XTREG,FE 'by hand' with firm dummies, or with 'areg'). An excellent
> > guide to the DPD estimators is provided in Steve Bond's ``Dynamic
> > panel data models: a guide to microdata methods and practice",
> > available from EconPapers (CeMMAP working paper 09/02 at
> Institute for
> > Fiscal Studies): http://econpapers.repec.org I don't see
> that in the
> > presence of a LDV that you can successfully employ FE.
> >
> > Kit Baum, Boston College Economics baum@bc.edu
> > http://ideas.repec.org/e/pba1.html
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
>
> Martin Mathes
> Universität Trier
> FB IV - VWL
> Europäische Wirtschaftspolitik
> D-54286 Trier
> Tel.: ++49-651-201-2747, -2739
> Fax: ++49-651-201-3934
> e-mail: mathes@uni-trier.de
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/